At the recognition stage, we have a ``DFFS'' value, the 60-element key, and the
residue value of a fully normalized mug-shot image. First, if the ``DFFS''
value is above a threshold (specified by the user), the mug-shot image does
not contain a true face. In other words, it is quite far from the cloud of
faces in our training set and should probably be discarded from the
recognition algorithm. Recall the face localization procedure presented in
Chapter 3. It is possible that the face localization incorrectly converges to
an image that is not a face. The detection process described in Chapter 3 only
dealt with blobs and limbs. This simplistic description of image data allows
us to detect faces in many poses, although this flexibility might also permit
a non-face to be falsely detected by the algorithm. A soccer-ball, for
example, might look like a face with two eyes, a mouth and a nose (from a simple
blob and limb description of the image). Since the face-detection scheme described
on Chapter 3 is based exclusively on a simple blob and limb description of the
image, the recognition stage might obtain a mug-shot of a soccer ball or other
non-face object. However, in the recognition stage, we utilize the
statistically based ``distance to face-space'' measurement to ultimately
reject non-face mug-shots from the localization procedure. Thus, the mug-shots
generated by the face-localization process can be filtered with a threshold on
their ``DFFS'' value before recognition is attempted.
Equation illustrates the use of a threshold on the
``DFFS'' value to prevent recognition attempts on non-faces. Typically, the
value used for
DFFSthreshold is roughly 3000.